Several described growth factors influence the proliferation and regeneration of the intestinal epithelium. Using a transgenic mouse model, we identified a human gene, R-spondin1, with potent and specific proliferative effects on intestinal crypt cells. Human R-spondin1 (hRSpo1) is a thrombospondin domain-containing protein expressed in enteroendocrine cells as well as in epithelial cells in various tissues. Upon injection into mice, the protein induced rapid onset of crypt cell proliferation involving beta-catenin stabilization, possibly by a process that is distinct from the canonical Wnt-mediated signaling pathway. The protein also displayed efficacy in a model of chemotherapy-induced intestinal mucositis and may have therapeutic application in gastrointestinal diseases.

Germplasm, genetics, phenotyping, and selection, combined with a clear definition of product targets, are the foundation of successful hybrid maize breeding. Breeding maize hybrids with superior yield for the drought-prone regions of the US corn-belt involves integration of multiple drought-specific technologies together with all of the other technology components that comprise a successful maize hybrid breeding programme. Managed-environment technologies are used to enable scaling of precision phenotyping in appropriate drought environmental conditions to breeding programme level. Genomics and other molecular technologies are used to study trait genetic architecture. Genetic prediction methodology was used to breed for improved yield performance for drought-prone environments. This was enabled by combining precision phenotyping for drought performance with genetic understanding of the traits contributing to successful hybrids in the target drought-prone environments and the availability of molecular markers distributed across the maize genome. Advances in crop growth modelling methodology are being used to evaluate the integrated effects of multiple traits for their combined effects and evaluate drought hybrid product concepts and guide their development and evaluation. Results to date, lessons learned, and future opportunities for further improving the drought tolerance of maize for the US corn-belt are discussed.

A successful strategy for prediction of crop yield that accounts for the effects of genotype and environment will open up many opportunities for enhancing the productivity of agricultural systems. Crop growth models (CGMs) have a history of application for crop management decision support. Recently whole genome prediction (WGP) methodologies have been developed and applied in breeding to enable prediction of crop traits for new genotypes and thus increase the size of plant breeding programs without the need to expand expensive field testing. The presence of Genotype-by-Environment-by-Management (G×E×M) interactions for yield presents a significant challenge for the development of prediction technologies for both product development by breeding and product placement within agricultural production systems. The integration of a CGM into the algorithm for whole genome prediction WGP, referred to as CGM-WGP, has opened up the potential for prediction of G×E×M interactions for breeding and product placement applications. Here a combination of simulation and empirical studies are used to explain how the CGM-WGP methodology works and to demonstrate successful reduction to practice for applications to maize breeding and product placement recommendation in the US corn belt.

A Crop Growth Model (CGM) is used to demonstrate a biophysical framework for predicting grain yield outcomes for Genotype by Environment by Management (G×E×M) scenarios. This required development of a CGM to encode contributions of genetic and environmental determinants of biophysical processes that influence key resource (radiation, water, nutrients) use and yield-productivity within the context of the target agricultural system. Prediction of water-driven yield-productivity of maize for a wide range of G×E×M scenarios in the U.S. corn-belt is used as a case study to demonstrate applications of the framework. Three experimental evaluations are conducted to test predictions of G×E×M yield expectations derived from the framework: (1) A maize hybrid genetic gain study, (2) A maize yield potential study, and (3)A maize drought study. Examples of convergence between key G×E×M predictions from the CGM and the results of the empirical studies are demonstrated. Potential applications of the prediction framework for design of integrated crop improvement strategies are discussed. The prediction framework opens new opportunities for rapid design and testing of novel crop improvement strategies based on an integrated understanding of G×E×M interactions. Importantly the CGM ensures that the yield predictions for the G×E×M scenarios are grounded in the biophysical properties and limits of predictability for the crop system. The identification and delivery of novel pathways to improved crop productivity can be accelerated through use of the proposed framework to design crop improvement strategies that integrate genetic gains from breeding and crop management strategies that reduce yield gaps.

Background and Aims Interleukin‐22 has beneficial effects on inflammation and impaired hepatic regeneration that characterize alcohol‐associated hepatitis (AH). F‐652 is a recombinant fusion protein of human interleukin‐22 and immunoglobulin G2 fragment crystallizable. This study aims to assess the safety and efficacy signals of F‐652 in patients with moderate and severe AH. Approach and Results A phase‐2 dose‐escalating study was carried out. F‐652 (10 μg/kg, 30 μg/kg, or 45 μg/kg) administered on days 1 and 7 was tested in 3 patients each with moderate (Model for End‐Stage Liver Disease [MELD] scores: 11‐20) and severe AH (MELD scores: 21‐28). Safety was defined by absence of serious adverse events and efficacy was assessed by Lille score, changes in MELD score, and serum bilirubin and aminotransferases at days 28 and 42. Three independent propensity‐matched comparator patient cohorts were used. Plasma extracellular vesicles and multiplex serum cytokines were measured to assess inflammation and hepatic regeneration. Eighteen patients (9 moderate and 9 severe AH) were enrolled, 66% were male, and the mean age was 48 years. The half‐life of F‐652 following the first dose was 61‐85 hours. There were no serious adverse events leading to discontinuation. The MELD score and serum aminotransferases decreased significantly at days 28 and 42 from baseline (P < 0.05). Day‐7 Lille score was 0.45 or less in 83% patients as compared with 6%, 12%, and 56% among the comparator cohorts. Extracellular vesicle counts decreased significantly at day 28 (P < 0.013). Cytokine inflammatory markers were down‐regulated, and regeneration markers were up‐regulated at days 28 and 42. Conclusions F‐652 is safe in doses up to 45 μg/kg and associated with a high rate of improvement as determined by Lille and MELD scores, reductions in markers of inflammation and increases in markers of hepatic regeneration. This study supports the need for randomized placebo‐controlled trials to test the efficacy of F‐652 in AH.

Key message Climate change and Genotype-by-Environment-by-Management interactions together challenge our strategies for crop improvement. Research to advance prediction methods for breeding and agronomy is opening new opportunities to tackle these challenges and overcome on-farm crop productivity yield-gaps through design of responsive crop improvement strategies. Abstract Genotype-by-Environment-by-Management (G × E × M) interactions underpin many aspects of crop productivity. An important question for crop improvement is “How can breeders and agronomists effectively explore the diverse opportunities within the high dimensionality of the complex G × E × M factorial to achieve sustainable improvements in crop productivity?” Whenever G × E × M interactions make important contributions to attainment of crop productivity, we should consider how to design crop improvement strategies that can explore the potential space of G × E × M possibilities, reveal the interesting Genotype–Management (G–M) technology opportunities for the Target Population of Environments (TPE), and enable the practical exploitation of the associated improved levels of crop productivity under on-farm conditions. Climate change adds additional layers of complexity and uncertainty to this challenge, by introducing directional changes in the environmental dimension of the G × E × M factorial. These directional changes have the potential to create further conditional changes in the contributions of the genetic and management dimensions to future crop productivity. Therefore, in the presence of G × E × M interactions and climate change, the challenge for both breeders and agronomists is to co-design new G–M technologies for a non-stationary TPE. Understanding these conditional changes in crop productivity through the relevant sciences for each dimension, Genotype, Environment, and Management, creates opportunities to predict novel G–M technology combinations suitable to achieve sustainable crop productivity and global food security targets for the likely climate change scenarios. Here we consider critical foundations required for any prediction framework that aims to move us from the current unprepared state of describing G × E × M outcomes to a future responsive state equipped to predict the crop productivity consequences of G–M technology combinations for the range of environmental conditions expected for a complex, non-stationary TPE under the influences of climate change.

OBJECTIVES:Andrographis paniculata has in vitro inhibitory activity against TNF-α, IL-1β and NF-κB. A pilot study of A. paniculata extract (HMPL-004) suggested similar efficacy to mesalamine for ulcerative colitis.METHODS:A randomized, double-blind, placebo-controlled trial evaluated the efficacy of A. paniculata extract (HMPL-004) in 224 adults with mild-to-moderate ulcerative colitis. Patients were randomized to A. paniculata extract (HMPL-004) 1,200 mg or 1,800 mg daily or placebo for 8 weeks.RESULTS:In total, 45 and 60% of patients receiving A. paniculata 1,200 mg and 1,800 mg daily, respectively, were in clinical response at week 8, compared with 40% of those who received placebo (P=0.5924 for 1,200 mg vs. placebo and P=0.0183 for 1,800 mg vs. placebo). In all, 34 and 38% of patients receiving A. paniculata 1,200 mg and 1,800 mg daily, respectively, were in clinical remission at week 8, compared with 25% of those who received placebo (P=0.2582 for 1,200 mg vs. placebo and P=0.1011 for 1,800 mg vs. placebo). Adverse events developed in 60 and 53% of patients in the A. paniculata 1,200 mg and 1,800 mg daily groups, respectively, and 60% in the placebo group.CONCLUSIONS:Patients with mildly to moderately active ulcerative colitis treated with A. paniculata extract (HMPL-004) at a dose of 1,800 mg daily were more likely to achieve clinical response than those receiving placebo.

No abstract